Chaos, Percolation and the Coronavirus Spread

The dynamics of the spreading of the COVID-19 virus has similar features to turbulent flow, chaotic maps, and other non-linear systems: a small seed grows exponentially and eventually saturates. Like in the percolation model, the virus is most dangerous if the probability of transmission (or the bond probability p in the percolation model) is high. This suggests a relation with the population density, ρs, which must be higher than a certain value (ρs > 1,000 persons/km2). A "seed' implanted in such populations grows vigorously and affects nearby places at distance x. Thus, the spreading is governed by the ratio ρ = ρs/x. Assuming a power law dependence τ of the number of positives to the virus N+ from ρ, we find τ = 0.55, 0.75, and 0.96 for South Korea, Italy, and China, respectively

Measurement of leakage neutron spectra with D-T neutrons and evaluated nuclear data

Benchmarking of evaluated neutron nuclear data libraries was performed for ∼14.8 MeV neutrons on the several targets, such as gallium, graphite, silicon carbide, uranium and tungsten samples. The experiments were performed at China Institute of Atomic Energy (CIAE). The neutron leakage spectra from the samples were measured at 60◦ and 120◦ by a TOF technique with a BC501A scintillation detector. The measured spectra are rather well reproduced by MCNP-4C simulations with the CENDL3.1, JENDL-4.0 and the new release ENDF/B-VIII.0, JEFF-3.3 evaluated nuclear data libraries and so on. There have some difference between experiments and simulations for the elastic and inelastic contributions in the partial energy range. And the discrepancies of the neutron leakage spectra in the MCNP simulations originate simply from the differences in the spectra distributions of the neutron reaction channels in the evaluated nuclear data libraries

Measurement of leakage neutron spectra with D-T neutrons and evaluated nuclear data

Benchmarking of evaluated neutron nuclear data libraries was performed for ∼14.8 MeV neutrons on the several targets, such as gallium, graphite, silicon carbide, uranium and tungsten samples. The experiments were performed at China Institute of Atomic Energy (CIAE). The neutron leakage spectra from the samples were measured at 60◦ and 120◦ by a TOF technique with a BC501A scintillation detector. The measured spectra are rather well reproduced by MCNP-4C simulations with the CENDL3.1, JENDL-4.0 and the new release ENDF/B-VIII.0, JEFF-3.3 evaluated nuclear data libraries and so on. There have some difference between experiments and simulations for the elastic and inelastic contributions in the partial energy range. And the discrepancies of the neutron leakage spectra in the MCNP simulations originate simply from the differences in the spectra distributions of the neutron reaction channels in the evaluated nuclear data libraries

The genome of a Mongolian individual reveals the genetic imprints of Mongolians on modern human populations

Mongolians have played a significant role in modern human evolution, especially after the rise of Genghis Khan (1162[?]–1227). Although the social cultural impacts of Genghis Khan and the Mongolian population have been well documented, explorations of their genome structure and genetic imprints on other human populations have been lacking. We here present the genome of a Mongolian male individual. The genome was de novo assembled using a total of 130.8-fold genomic data produced from massively parallel whole-genome sequencing. We identified high-confidence variation sets, including 3.7 million single nucleotide polymorphisms (SNPs) and 756,234 short insertions and deletions. Functional SNP analysis predicted that the individual has a pathogenic risk for carnitine deficiency. We located the patrilineal inheritance of the Mongolian genome to the lineage D3a through Y haplogroup analysis and inferred that the individual has a common patrilineal ancestor with Tibeto-Burman populations and is likely to be the progeny of the earliest settlers in East Asia. We finally investigated the genetic imprints of Mongolians on other human populations using different approaches. We found varying degrees of gene flows between Mongolians and populations living in Europe, South/Central Asia, and the Indian subcontinent. The analyses demonstrate that the genetic impacts of Mongolians likely resulted from the expansion of the Mongolian Empire in the 13th century. The genome will be of great help in further explorations of modern human evolution and genetic causes of diseases/traits specific to Mongolians